Base editors are dedicated engineered deaminases that enable directed conversion of specific bases in the genome or transcriptome in a precise and efficient manner, and hold promise for correcting pathogenic… Click to show full abstract
Base editors are dedicated engineered deaminases that enable directed conversion of specific bases in the genome or transcriptome in a precise and efficient manner, and hold promise for correcting pathogenic mutations. A major concern limiting application of this powerful approach is the issue of off-target edits. Several recent studies have shown substantial off-target RNA activity induced by base editors and demonstrated that off-target mutations may be suppressed by improved deaminases versions or optimized guide RNAs. Here we describe a new class of off-target events that are invisible to the established methods for detection of genomic variations, and were thus far overlooked. We show that much of the off-target activity of the deaminases is nonspecific, seemingly stochastic, affecting a large number of sites throughout the genome or the transcriptome and accounting for the majority of off-target activity. We develop and employ a different, complementary, approach that is sensitive to the stochastic off-targets activity, and use it to quantify the abundant off-target RNA mutations due to current optimized deaminase editors. Engineered base editors enable directed manipulation of the genome or transcriptome at single-base resolution. We believe that implementation of this computational approach would facilitate design of more specific base editors. We provide a computational tool to quantify global off-target activity, which can be used to optimize future base editors.
               
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